Evaluating different methods of serum collection to detect failed transfer of passive immunity in newborn calves via refractometry
Bibliographic record
Abstract
The objective of the study was to compare 4 different methods of serum collection to assess failed transfer of passive immunity (FTPI) in dairy calves. We hypothesized that centrifuged serum, filtered serum and clotted serum at room temperature, and clotted serum at refrigerator temperature measured with Brix refractometry would highly correlate with IgG concentration assessed by radial immunodiffusion (RID; gold standard) in centrifuged serum. Blood samples were collected from 321 newborn dairy calves. In centrifuged serum (r = 0.88), serum clotted at room temperature (20.2°C ± 6.47; r = 0.86), serum clotted at refrigerator temperature (7.6°C ± 0.91; r = 0.87), and filtered serum (r = 0.70), total solids (TS) in % Brix, and IgG concentrations measured with RID were highly correlated. Regarding the refractometry results among the different serum types, the TS results of serum clotted at room temperature, clotted at refrigerator temperature, and filtered serum showed high correlation coefficients compared with the TS results of centrifuged serum (r = 0.99, r = 0.98, and r = 0.89), respectively. The test characteristics of clotted serum were as accurate as centrifuged serum and generate comparable results. Filtered serum was slightly less accurate. All serum types are valid methods to detect an FTPI in dairy calves, if the specific Brix thresholds for each serum type are considered. Nevertheless, serum clotted at refrigerator temperature should not be the preferred method to avoid the risk of hemolysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".